{"title":"Extract, model, refine: improved modelling of program verification tools through data enrichment.","authors":"Sophie Lathouwers, Yujie Liu, Vadim Zaytsev","doi":"10.1007/s10270-024-01232-7","DOIUrl":null,"url":null,"abstract":"<p><p>In software engineering, models are used for many different things. In this paper, we focus on program verification, where we use models to reason about the correctness of systems. There are many different types of program verification techniques which provide different correctness guarantees. We investigate the domain of program verification tools and present a concise megamodel to distinguish these tools. We also present a data set of 400+ program verification tools. This data set includes the category of verification tool according to our megamodel, practical information such as input/output format, repository links and more. The practical information, such as last commit date, is kept up to date through the use of APIs. Moreover, part of the data extraction has been automated to make it easier to expand the data set. The categorisation enables software engineers to find suitable tools, investigate alternatives and compare tools. We also identify trends for each level in our megamodel. Our data set, publicly available at https://doi.org/10.4121/20347950, can be used by software engineers to enter the world of program verification and find a verification tool based on their requirements. This paper is an extended version of https://doi.org/10.1145/3550355.3552426.</p>","PeriodicalId":49507,"journal":{"name":"Software and Systems Modeling","volume":"24 4","pages":"1293-1313"},"PeriodicalIF":3.2000,"publicationDate":"2025-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12289842/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Software and Systems Modeling","FirstCategoryId":"94","ListUrlMain":"https://doi.org/10.1007/s10270-024-01232-7","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/8 0:00:00","PubModel":"Epub","JCR":"Q3","JCRName":"COMPUTER SCIENCE, SOFTWARE ENGINEERING","Score":null,"Total":0}
引用次数: 0
Abstract
In software engineering, models are used for many different things. In this paper, we focus on program verification, where we use models to reason about the correctness of systems. There are many different types of program verification techniques which provide different correctness guarantees. We investigate the domain of program verification tools and present a concise megamodel to distinguish these tools. We also present a data set of 400+ program verification tools. This data set includes the category of verification tool according to our megamodel, practical information such as input/output format, repository links and more. The practical information, such as last commit date, is kept up to date through the use of APIs. Moreover, part of the data extraction has been automated to make it easier to expand the data set. The categorisation enables software engineers to find suitable tools, investigate alternatives and compare tools. We also identify trends for each level in our megamodel. Our data set, publicly available at https://doi.org/10.4121/20347950, can be used by software engineers to enter the world of program verification and find a verification tool based on their requirements. This paper is an extended version of https://doi.org/10.1145/3550355.3552426.
期刊介绍:
We invite authors to submit papers that discuss and analyze research challenges and experiences pertaining to software and system modeling languages, techniques, tools, practices and other facets. The following are some of the topic areas that are of special interest, but the journal publishes on a wide range of software and systems modeling concerns:
Domain-specific models and modeling standards;
Model-based testing techniques;
Model-based simulation techniques;
Formal syntax and semantics of modeling languages such as the UML;
Rigorous model-based analysis;
Model composition, refinement and transformation;
Software Language Engineering;
Modeling Languages in Science and Engineering;
Language Adaptation and Composition;
Metamodeling techniques;
Measuring quality of models and languages;
Ontological approaches to model engineering;
Generating test and code artifacts from models;
Model synthesis;
Methodology;
Model development tool environments;
Modeling Cyberphysical Systems;
Data intensive modeling;
Derivation of explicit models from data;
Case studies and experience reports with significant modeling lessons learned;
Comparative analyses of modeling languages and techniques;
Scientific assessment of modeling practices